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Oxford secures Innovate UK funding to use AI to improve diagnosis

Greg Clark, UK Secretary of State for Business, Energy and Industrial Strategy (BEIS), will confirm today (Tuesday 6 November) that UK Research and Innovation will invest £10million in the National Consortium of Intelligent Medical Imaging (NCIMI), to be led from Oxford University as part of the Industrial Strategy Challenge Fund.

NCIMI will also benefit from a further £5 million of funding provided from its commercial partners, which include a range of local SMEs and University spin outs and large national and international companies (GE Healthcare and Alliance Medical).

The funding was provided through the Government’s modern industrial strategy by Innovate UK, part of UK Research and Innovation, as part of the £50m investment to establish a network of digital pathology, imaging and Artificial Intelligence (AI) centres, to drive innovation in the use of AI for improved diagnosis and delivery of precision treatments.

NCIMI will support the development of an ecosystem for AI in medical imaging. It will enable a pipeline of algorithms to be developed from bench to bedside in a hospital and university network partnered with commercial collaborators for the benefit of NHS patients. The consortium will provide the infrastructure for today and tomorrow’s SMEs working in medical imaging AI to flourish.

The consortium includes a range of NHS Trusts from across the country, SMEs and global industry partners and will have a physical base within the University of Oxford Big Data Institute.

NCIMI will provide tangible results for patients through the innovative use of AI in medical imaging across MRI, CT, PET-CT, X-Ray and ultrasound. These technologies will be aiding in the early detection, diagnosis, and monitoring of diseases.

Some of the key exemplars for the development and transfer to the NHS that the NCIMI will be working on delivering will be:

Early detection of cardiovascular disease

Patient involvement in early preventive medical advice at scale for genetic diseases, typified by haemochromatosis

Central to the consortium’s work will be the development of a sustainable platform to enable further innovation and frameworks for NHS adoption of the technologies.

Professor Gavin Screaton, Head of the University of Oxford Medical Sciences Division said “We are delighted that Innovate UK has chosen to support our National Consortium. We believe that combining the heath data, ethics, clinical and AI expertise within the University with a national NHS network and a range of industry partners has real potential to introduce new solutions which will improve patient care”.

Professor Fergus Gleeson, NCIMI Executive Clinician Scientist and Group Leader in the Department of Oncology, said, “I am very much looking forward to working with our NHS, University and industry partners to promote the development and implementation of AI into the NHS and medical care around the world”.

“Partnership is critical to successful development and deployment of Artificial Intelligence technology,” said Todd McNitt, GM of Digital Solutions at GE Healthcare. “We are proud to work alongside leading academic institutions like Oxford University as well as local SMEs, NHS hospitals and other industry partners to bring the promise of AI-enabled precision health to patients across the UK and around the world.”

Professor Sir Michael Brady, Executive Chairman of NCIMI and Founder of Perspectum Diagnostics, Director of Mirada Medical and Chairman of Optellum commented “All of the Oxford-based SMEs are excited to be part of the consortium working alongside industry and other partners to support the development and use of AI in healthcare. We hope that these developments will benefit patient treatment and patient pathways in the NHS.”

“The centres announced today bring together the teams that will develop artificial intelligence tools that can analyse medical images varying from x-rays to microscopic sections from tissue biopsies. Artificial intelligence has the potential to revolutionise the speed and accuracy of medical diagnosis.”